Stochastic Simulation Of Dopamine Neuromodulation For Implementation Of Fluorescent Neurochemical Probes In The Striatal Extracellular Space

Imaging the dynamic behavior of neuromodulatory neurotransmitters in the extracelluar space arising from individual quantal releases would constitute a major advance in neurochemical imaging. Spatial and temporal resolution of these highly stochastic neuromodulatory events requires concurrent advances in the chemical development of optical nanosensors selective for neuromodulators in concert with advances in imaging methodologies to capture millisecond neurotransmitter release. Herein, we develop and implement a stochastic model to describe dopamine dynamics in the extracellular space (ECS) of the brain dorsal striatum. Our model is developed from first principles and simulates release, diffusion, and reuptake of dopamine in a 3D simulation volume of striatal tissue. We find that in vivo imaging of neuromodulation requires simultaneous optimization of dopamine nanosensor reversibility and sensitivity: dopamine imaging in the striatum or nucleus accumbens requires nanosensors with an optimal dopamine dissociation constant (Kd) of 1 M, whereas Kd above 10 M are required for dopamine imaging in the prefrontal cortex. Furthermore, our model reveals that imaging frame rates of 20 Hz are optimal for imaging temporally-resolved dopamine release events based on the probabilistic nature of dopaminergic terminal activity in the striatum. Our work provides a modeling platform to probe how complex neuromodulatory processes can be studied with fluorescent nanosensors and enables direct evaluation of nanosensor chemistry and imaging hardware parameters. Our stochastic model is generic for evaluating fluorescent neurotransmission probes, and is broadly applicable to the design of other neurotransmitter fluorophores and their optimization for implementation in vivo.